A dog on a walk is pulled toward interesting smells, squirrels and passers-by, while the leash sets a hard physical limit on how far it can wander from the handler. This scene models that tug-of-war from directly overhead: the handler follows a circular path, a wandering "distraction" pulls the dog outward, and the leash goes taut the instant the dog reaches the end of its slack.
Stop-and-go (also called "be a tree") works because it removes the dog's reward — forward movement toward the distraction — the instant it pulls, then restores that reward only for loose-leash position. Most dogs learn the pattern within a few dozen repetitions.
A top-down 3D walk where a wandering distraction pulls a dog outward while the leash sets a hard limit — switch training methods and watch pulling behavior improve or worsen over time.
Leash tension turns from loose (green) to taut (red) the instant the dog nears leash length. Under "no correction" the handler keeps walking through a taut leash, reinforcing pulling; stop-and-go and treat reinforcement instead reward loose-leash position.
Adjust distraction drive, leash length and walking speed, then switch training methods and watch the walk quality score and leash tension respond as the dog and handler interact in real time.
Stop-and-go ("be a tree") works purely through negative punishment — removing forward motion the moment the dog pulls — with no leash correction needed at all.